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A potential field shared control approach for wheelchair navigation via brain-computer interface.

Yuchen Xia1, Yuxuan Wei1, Songwei Li1

  • 1State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University, Shanghai, People's Republic of China.

Journal of Neural Engineering
|December 15, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a novel shared control system for brain-controlled wheelchairs (BCWs) that significantly improves navigation in narrow spaces. The new system enhances wheelchair control performance and success rates for individuals with disabilities.

Keywords:
artificial potential fields (APFs)brain–computer interface (BCI)motor imagery (MI)shared controlwheelchair control

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Area of Science:

  • Neuroscience
  • Robotics
  • Rehabilitation Engineering

Background:

  • Electroencephalography (EEG)-based brain-computer interfaces (BCIs) offer potential for individuals with disabilities to control external devices.
  • Limitations in EEG signal quality can hinder the performance of BCIs, particularly for complex tasks like wheelchair navigation.
  • Existing brain-controlled wheelchairs (BCWs) struggle with flexible movement in confined or narrow environments.

Purpose of the Study:

  • To develop and evaluate a shared controller for BCWs that integrates EEG decoding with environmental information.
  • To enhance the flexible movement capabilities of BCWs, especially in challenging narrow spaces.
  • To compare the performance of the proposed shared control system against BCI-only control and traditional keyboard control.

Main Methods:

  • A shared controller was designed using the potential field method, fusing EEG decoding results (motor imagery paradigm) with environmental data.
  • A virtual wheelchair navigation experiment was conducted with 12 subjects, and a real-world experiment with 5 subjects.
  • Control performance was assessed under three modes: keyboard control, BCI-only control, and the proposed shared control.

Main Results:

  • The shared controller significantly improved navigation performance in both general and narrow environments compared to BCI-only control.
  • Success rates in virtual complex environments increased from 8.33% to 83.33%, and in real-world two-way navigation from 23.33% to 66.67%.
  • Shared control achieved success rates comparable to keyboard control (p>0.05) and reduced average navigation time by nearly 100 seconds in real-world tests.

Conclusions:

  • The proposed shared control method enhances the maneuverability of BCWs in difficult, narrow environments.
  • This approach offers a promising solution for improving the independence and quality of life for individuals with mobility impairments.
  • Shared control represents a significant advancement in BCW technology, addressing limitations of current BCI systems.